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Assessing the Societal Impacts of Emerging Distributed Intelligence Technologies

Assessing the Societal Impacts of Emerging Distributed Intel...

2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Khan, Irfan Alekhya, V. Rajalakshmi, B. Lakhanpal, Sorabh Alkhafaji, Mohammed Ayad Santhi, K. Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Computer Science Bangalore India Lovely Professional University Phagwara India National University of Science and Technology College of Technical Engineering Dhi Qar64001 Iraq St. Martin's Engineering College Dept. of It Telangana Secunderabad India

ISBN: (纸本)9798350373783

The Integrated Impact Assessment Framework (iiAF) is established in this study to examine how new distributed intelligence technologies (DIT) influence society. The framework comprises three powerful algorithms: SNDA, EIS, and EIAM. These illustrate DIT's various benefits. SNDA examines the complex social web, identifying hubs, community dynamics, and future trends. EIS predicts economic repercussions and provides GDP, expenditures, and job losses. computer faults and privacy are important ethical considerations for EIAM. These strategies paint a comprehensive picture of the effect. Fake data suggests the new strategy outperforms six others. The recommended strategy scores higher on significance, economic indicators, and ethics. The iiAF's DIT impact evaluation is more complete, educated, and responsible than other techniques. This work contributes to our understanding of the problem by proposing a flexible and resilient paradigm for dealing with the societal consequences of diverse technologies. The iiAF may demonstrate to politicians the immediate impacts of DIT adoption and discuss morality and society. The framework's holistic approach helps us understand how technology and society interact and evolve. © 2024 IEEE.

关键词： Inflation

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Novel method for robust bilateral filtering point cloud denoising

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Alexandria Engineering Journal 2025年 127卷 573-585页

作者： Yang, Huan Wang, Wei Wang, Yue Wang, Peng College of Computer Science and Technology Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Chongqing Nan'an400065 China School of Advanced Manufacturing Engineering Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Chongqing Nan'an400065 China Sevnce Robotics Co. Ltd Building 7 Phase II Internet Industrial Park Chongqing Liangjiang401123 China Big Data Institute BaoShan University No. 16 Yuanzheng Road Longyang District Yunnan Baoshan678000 China

Bilateral filtering for point cloud denoising relies on the normal of the points. However, normals are not inherent attributes of point clouds but are estimated using algorithms such as principal component analysis (PCA). Due to inaccuracies in the normals, bilateral filtering may lead to unexpected results, such as smoothing in sharp regions. This study addressed this issue by improving the accuracy of normals. Initially, PCA was employed to estimate the initial normals of the point cloud. The points were then categorized into edge and planar points by fitting a three-dimensional sphere. Subsequently, iterative weighted PCA was applied to refine the normals of the edge points. Finally, the improved normals were integrated into bilateral filtering to achieve point cloud denoising. Additionally, a robust estimator was used instead of a Gaussian function to compute the weights in the bilateral filtering. To assess and compare the performance of this algorithm with related ones, the mean square angular error (MSAE) and angular error distribution (AE) were employed to evaluate the accuracy of normal estimation, while the mean square error (MSE) and signal-to-noise ratio (SNR) were employed to assess the denoising performance. Results indicate that the proposed method yielded the most accurate normals compared to PCA, Jet, and VCM normal estimation algorithms. Moreover, when compared to algebraic point set surfaces (APSS), robust implicit moving least squares (RIMLS), anisotropic weighted locally optimal projection (AWLOP), bilateral filtering, and guided filtering point cloud denoising algorithms, the proposed method consistently achieved the smallest MSE and the highest SNR in most cases on the dataset used in this study. © 2025 The Authors

关键词： Principal component analysis

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Advanced Development on Real Time Monitoring of Bridges Using Wireless Fidelity 7

Advanced Development on Real Time Monitoring of Bridges Usin...

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7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Ferlin Deva Shahila, D. Stephen, Valantina Padma Suresh, L. Ashwini, A. Shally, S.P. Anushia, R.M. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of ECE Chennai India Saveetha School of Engineering Department of EEE Chennai Thandalam India Baselios Mathews II College of Engineering Computer Science and Engineering Kollam India DMI College of Engineering Department of ECE Chennai India DMI College of Engineering Department of CSE Chennai India

ISBN: (纸本)9798350372816

Wireless fidelity technology enables communication without the use of wires or connections between two or more people across large distances. Wireless technology encompasses communications that utilize both radio frequencies (RF) and infrared waves. The origin of wireless technology can be traced back to the invention of electromagnetic waves by the German physicist, geophysicist, and engineer, Heinrich Hertz. In the late nineteenth century, the commercial wireless telegraph service was established by the Italian entrepreneur Gugliello Marconi, more than half a century after the invention of the first commercially available wired telegraph in 1832. In the early twentieth century, Marconi was one of the pioneers of radio communications, transmitting radio signals to mobile receivers on ships. Wireless has always been more advanced than wired technology, and it's usually more expensive too, but it's also given us the added benefit of being able to move around and get and send *** this project, we'll be using MATLAB software to design and test the full model. We'll also be looking at wireless bridge health monitoring systems. ZigBee acts as the wireless network for short-range IEEE 802.11 communication between sensors in the bridge. © 2024 IEEE.

关键词： Zigbee

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Advanced Simulation and Optimization Strategies in Thermo-Fluid Dynamics: A Deep Learning Approach to Enhancing Heat Transfer in Evaporative Cooling Systems

Advanced Simulation and Optimization Strategies in Thermo-Fl...

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2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Rajalakshmi, B. Alekhya, V. Lakhanpal, Sorabh Khan, Irfan Munshid, Maha Chasib Maranan, Ramya New Horizon College of Engineering Department of Computer Science Bangalore India Institute of Aeronautical Engineering Hyderabad Dundigal India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India National University of Science and Technology Collage of Nursing Dhi Qar64001 Iraq Simats Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350373783

This article describes a novel technique to study and improve evaporative cooling systems to move heat better. The system uses the GA, CNN, LSTM, and FVM algorithms. Each thermofluid dynamics study approach provides something unique. The CNN approach independently acquires spatial information from raw modeling data to study fluid movement. Temporal linkages in sequential data reveal heat's movement over space and time via LSTM. GAN adds continuing antagonistic processes to the dataset, strengthening the model. GA adjusts GAN settings to improve data, whereas FVM simulates realistic fluid dynamics to improve heat transport. Ablation studies demonstrate each algorithm's distinct contributions and importance. Performance comparisons reveal that the recommended framework outperforms others in accuracy, processing time, memory utilization, convergence rate, resilience, and adaptability. Bar charts, line charts, pie charts, and histograms show how the recommended method compares to others. The framework is precise, efficient, and versatile, making it ideal for improving thermo-fluid dynamics models in evaporative cooling systems. Researchers and engineers seeking to improve heat transfer in evaporative cooling systems can utilize it. The proposed architecture is full and adaptable to thermal-fluid utilization issues. © 2024 IEEE.

关键词： Evaporative cooling systems

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Multispectral Imaging for Differential Face Morphing Attack Detection: A Preliminary Study

Multispectral Imaging for Differential Face Morphing Attack ...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Raghavendra Ramachandra Sushma Venkatesh Naser Damer Narayan Vetrekar R. S. Gad Norwegian University of Science and Technology (NTNU) Gjøvik Norway AiBA AS Gjøvik Norway Fraunhofer Institute for Computer Graphics Research Germany School of Physical and Applied Sciences Goa University Goa India

Face morphing attack detection is emerging as an increasingly challenging problem owing to advancements in high-quality and realistic morphing attack generation. Reliable detection of morphing attacks is essential because these attacks are targeted for border control applications. This paper presents a multispectral framework for differential morphing-attack detection (D-MAD). The D-MAD methods are based on using two facial images that are captured from the ePassport (also called the reference image) and the trusted device (for example, Automatic Border Control (ABC) gates) to detect whether the face image presented in ePassport is morphed. The proposed multi-spectral D-MAD framework introduce a multispectral image captured as a trusted capture to acquire seven different spectral bands to detect morphing attacks. Extensive experiments were conducted on the newly created Multispectral Morphed Datasets (MSMD) with 143 unique data subjects that were captured using both visible and multispectral cameras in multiple sessions. The results indicate the superior performance of the proposed multispectral framework compared to visible images.

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Real-time Settings and Their Transformation through Distributed Intelligence Communication Technologies

Real-time Settings and Their Transformation through Distribu...

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2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Manjunatha Krishna, M. Hari Rai, Vijay Kumar Singh, Navdeep Kumar, Ashwani Habelalmateen, Mohammed I. New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Institute of Aeronautical Engineering Hyderabad Dundigal India Ies College of Technology Department of Computer Science & Engineering M. P Bhopal India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India The Islamic University Najaf Iraq

ISBN: (纸本)9798350373783

Modern real-time settings and dispersed intelligence communication technologies require new solutions to improve efficiency, flexibility, and scalability. This research introduces dynamic edge-cloud orchestration for real-time intelligence. The approach uses the Dynamic Task Allocation Algorithm (DTAA), the Predictive Resource Scaling Algorithm (PRSA), and the Adaptive Communication Routing Algorithm. DTAA distributes work between edge devices and the cloud based on priority, processing time, and resources. PRSA estimates future resource needs, making edge and cloud scaling easier. ACRA adjusts communication routes based on latency, job priority, and network circumstances. We use numbers to compare the new strategy to six popular ones. These include SDA, TFA, RBI, FBA, and PRT. The proposed option outperforms the others in latency, scalability, security, reliability, freedom, and resource utilization. Due to its comprehensive framework for smart task assignment, resource management, and communication enhancement, DECO-RTI is a major advance in real-time settings. The approach can adapt to changing situations and automatically scale up resources, making it ahead of the curve for distributed intelligent communication systems. © 2024 IEEE.

关键词： Scalability

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Comparison of SVM and Random Forest for Detection of Malicious Node in Wireless Sensor Networks 2

Comparison of SVM and Random Forest for Detection of Malicio...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Thamma, Sankara Reddy Gurumoorthi, E. Prakash, C. Om Muthusundar, S.K. Nidhya, M.S. Maram, Balajee Deloitte Consulting LLP 28027 United States DC Technical Delivery Master II Information Technology ConcordNC28027 United States School of Engineering Malla Reddy University India CMR University Bengaluru India Chennai Institute of Technology college Dept of AI & DS Chennai India School of Computer Applications Dayananda Sagar University Bangalore India School of Computer Science and Artificial Intelligence SR University Ananthasagar Hasanparthy Warangal India

ISBN: (纸本)9798331505745

Wireless Sensor Networks (WSNs) are used in various contexts and offer a wide range of applications, despite being a decentralized, resource-scarce network type;this is why this study deals with the problem of malicious nodes. Identifying such nodes is important to preventing the compromise of the network and all the nodes in it. In this paper, a comparative study of two popular classifiers named Support Vector Machine (SVM) and Random Forest (RF) in order to detect hostile nodes in WSNs. By nature, a malicious node in a network will cause significant problems to the users. There are number of models also there to detect the malicious node. Based on the above-discussed parameters the paper compares these algorithms in terms of detection accuracy, computational complexity, scalability and performance measure of imbalanced data. The comparison draws on different targets such as accuracy, capacity/large scale, speed, and small sample imbalance, and noise. As stated in this paper, both SVM and Random Forest have its own strengths where the selection between them mainly depends on the network environment and the features of the malicious activity. © 2025 IEEE.

关键词： Wireless sensor networks

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First Workshop on User Perspectives in Human-Centred Artificial Intelligence (HCAI4U) 23

First Workshop on User Perspectives in Human-Centred Artific...

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15th Biannual Conference of the Italian SIGCHI Chapter: Crossing HCI and AI, CHItaly 2023

作者： De Luca, Ernesto William Purificato, Erasmo Boratto, Ludovico Marrone, Stefano Sansone, Carlo Institute of Technical and Business Information Systems Human-Centred AI Group Otto von Guericke University Magdeburg Germany Department of Mathematics and Computer Science University of Cagliari Italy Dipartimento di Ingegneria Elettrica e Delle Tecnologie dell'Informazione University of Naples Federico II Italy

ISBN: (纸本)9798400708060

The emerging concept of Human-Centred Artificial Intelligence (HCAI) involves the amplification, augmentation, empowerment, and enhancement of individuals. The goal of HCAI is to ensure that AI meets our needs while also operating transparently, delivering fair and equitable outcomes, and respecting privacy, all while preserving human control. This approach involves multiple stakeholders, such as researchers, developers, business leaders, policy makers, and users, who are affected in various ways by the implementation and evaluation of AI systems. The primary focus of the First Workshop on User Perspectives in Human-Centred Artificial Intelligence (HCAI4U) is to examine the potential positive and negative impacts of automated decision-making systems on end-users, as well as how their interaction with AI is influenced by human-centred aspects of reliability, safety, and fairness. The workshop aims to facilitate discussion and exchange of ideas among the community on advances in developing trustworthy, fair, and privacy-preserving systems, as well as user interfaces that are explainable, with a specific focus on the users' perception in real-world scenarios rather than solely on the algorithmic and model performance. Additionally, HCAI4U aims to foster cross-disciplinary and interdisciplinary discussions between experts from various research fields, such as computer science, psychology, sociology, law, medicine, business, etc., to discuss problems and synergies in this exciting research topic. © 2023 Owner/Author.

关键词： Human computer interaction

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Light Direction Reconstruction Analysis and Improvement using XAI and CG 30

Light Direction Reconstruction Analysis and Improvement usin...

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30th International Conference in Central Europe on computer graphics, Visualization and computer Vision, WSCG 2022

作者： Miller, Markus Ronczka, Stefan Nischwitz, Alfred Westermann, Rüdiger Dept. of Computer Science and Mathematics University of Applied Sciences Munich Lothstr. 64 Bavaria MunichD-80335 Germany Computer Graphics and Visualization Technical University Munich Boltzmannstr. 3/II Bavaria GarchingD-85748 Germany w&co MediaServices GmbH & Co KG Charles-de-Gaulle-Str. 8 Bavaria MunichD-81737 Germany

ISBN: (纸本)9788086943336

With rapid advances in the field of deep learning, explainable artificial intelligence (XAI) methods were introduced to gain insight into internal procedures of deep neural networks. Information gathered by XAI methods can help to identify shortcomings in network architectures and image datasets. Recent studies, however, advise to handle XAI interpretations with care, as they can be unreliable. Due to this unreliability, this study uses meta information that is produced when applying XAI to enhance the architecture - and thus the prediction performance - of a recently published regression model. This model aimed to contribute to solving the photometric registration problem in the field of augmented reality by regressing the dominant light direction in a scene. Bypassing misleading XAI interpretations, the influence of synthetic training data, generated with different rendering techniques, is furthermore evaluated empirically. In conclusion, this study demonstrates how the prediction performance of the recently published model can be increased by improving the network architecture and training dataset. © 2022 University of West Bohemia. All rights reserved.

关键词： Network architecture

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Predicting Fish Habitat in the Persian Gulf Using Artificial Intelligence 1

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International Conference on Advances in Communication Technology and computer Engineering, ICACTCE 2023

作者： Hai, Tao Zhou, Jincheng Ahmadi, Hoorieh Ekiye, Ayibatonbo Ebiare Wei, Yangping Iwendi, Celestine Boulouard, Zakaria School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun558000 China School of Creative Technologies University of Bolton Bolton United Kingdom LIM Hassan II University of Casablanca Casablanca Morocco School of Information and Artificial Intelligence Nanchang Institute of Science and Technology Nanchang China

ISBN: (数字)9783031371646

ISBN: (纸本)9783031371639

The Persian Gulf is one of the most important habitats in the Middle East. It can be extremely beneficial to aquatic species’ survival and environmental preservation to continuous monitoring and collect data about aquatic animals, their habitats, and behaviours. Finding a novel and suitable method to carry out accurate and automatic monitoring with low timing and low cost for monitoring aquatic species’ behaviour in this high potential area is helpful. To predict fish habitat in Persian Gulf Convolutional Neural Network method and Naïve Bayes algorithm are used. Deep learning convolutional neural network technology is mostly used for data science classification and recognition because of its exceptional accuracy and to solve search and optimization issues, the Naïve Bayes algorithm is employed. Results indicate for predicting fish habitat in the Persian Gulf, the accuracy of the Convolutional Neural Network algorithm and the Naïve Bayes algorithms is 97.32% and 95.47%, respectively. With p = 0.025 (p0.05), there is a substantial difference between the Naïve Bayes method and the Convolutional Neural Network algorithm. Therefore, The Convolutional Neural Network method seems to be more accurate than the Naïve Bayes method at predicting fish habitat in the Persian Gulf. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Ecosystems

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